Five Steps for Digital Collaboration in Industrial Clusters 2025

9Scaling involves expanding pilots, adding features, involving more stakeholders and replicating successful projects. Success relies on continuous learning cycles to build a “cluster memory” that supports collaboration and business case development. Scaling can be approached as a one-off effort or as a systematic process where lessons learned from early stages make replication smoother and more efficient. Recommendations –Develop customized and inclusive strategies: Scaling efforts should accommodate the diverse needs of participants joining at different stages. This includes integrating industry, or cluster-specific requirements – whether shaped by regulations, technological maturity, or data availability – into the design, ensuring flexibility without compromising project success. –Strengthen capacity building and incentives: As projects scale, there needs to be enough capacity and appropriate incentives to support deployment across a broad range of cluster members of different sizes and sectors. This can be facilitated by the cluster convener or coordinated through the governance structure. –Embed learning cycles and standardization to enable replication: Embedding learning cycles and a replicability mindset makes scaling systematic and sustainable. Institutionalizing knowledge-sharing and learning frameworks can create a “cluster memory”, making future scaling efforts more efficient.Step 4: Scaling CASE STUDY 4 Standardization is the bridge between innovation and large-scale impact Embedding learning cycles and a replicability mindset is key to scaling digital initiatives systematically. By institutionalizing knowledge-sharing and creating a “cluster memory” future scaling efforts become more efficient and impactful. One example of this is the collaboration between Envision and the China National Institute of Standardization (CNIS) in developing the Construction Specification of Zero-Carbon Industrial Park, now an official local standard. Building on the cluster’s success, CNIS is working to establish national and international standards, ensuring global best practices can be replicated across industrial clusters. Standardization is the bridge between innovation and large-scale impact. By codifying best practices, we ensure that learnings from one project can drive transformation across entire industries – accelerating the transition to zero-carbon industrial ecosystems. Glenn Gu, Product and Development Senior Director, Envision Net-Zero Industrial Park The Ordos-Envision Net Zero Industrial Park: AIoT-enabled energy and carbon platform Background and objectives Digital technologies Results The Ordos-Envision Net Zero Industrial Park is attracting industries (such as EV and batteries manufacturing, renewable energy and hydrogen) to establish a green industrial park powered 80% by green electricity. The cluster uses an AIoT-integrated digital “Ark” platform to optimize energy production, storage and consumption in the cluster, cutting emissions and costs. –Internet of Things (IoT) data is integrated in real-time for energy- carbon accounting and analysis –AI and Machine Learning optimizes subsystem coupling, renewable redispatch, demand response and electricity trading to cut emissions and support net-zero goals –A Visualization and Collaboration Platform aggregates data from electricity, water and gas meters, enabling precise carbon accounting and full-process energy monitoringThanks to a digitally integrated energy system with 12 large-scale enterprises participating, the cluster: –Reduced by 10% energy costs for tenants –Cut CO2 by 100 million tons per year –Increased GDP by 300 billion yuan per year –Attracted industrial activity, providing tens of thousands of employment opportunities